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R analysis code complete

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Corentin Choisy
2024-01-26 15:46:13 +01:00
parent 30d95f324c
commit dc031bb138
3 changed files with 2111 additions and 58 deletions
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77
Scripts/Analysis/NoDIF/pcm_nodif_100.do
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@ -1,49 +1,54 @@
*=================================================================================================================================================
* Date : 2024-01-23
* Stata version : Stata 18 SE
*
* This program analyses simulated data without DIF through a partial credit model
*
* ado-files needed : - pcm (version 5.5 October 25, 2023, available on gitea)
*
* outputs : for N=100
*
*
*================================================================================================================================================
*=================================================================================================================================================
* Date : 2024-01-23
* Stata version : Stata 18 SE
*
* This program analyses simulated data without DIF through a partial credit model
*
* ado-files needed : - pcm (version 5.5 October 25, 2023, available on gitea)
*
* outputs : for N=100
*
*
*================================================================================================================================================
* Load pcm.ado
adopath+"/home/corentin/Documents/These/Recherche/Simulations/Modules/"
* Load pcm.ado
adopath+"/home/corentin/Documents/These/Recherche/Simulations/Modules/"
* Set output folder path
local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/NoDIF/N100"
local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N100"
local Nn = 100
* Set output folder path
local path_data = "/home/corentin/Documents/These/Recherche/Simulations/Data/DIF/N100"
local path_res = "/home/corentin/Documents/These/Recherche/Simulations/Analysis/NoDIF/N100"
local Nn = 100
*==========================
* Scenarios with : J=4
*==========================
*==========================
* Scenarios with : J=4
*==========================
** Scenario 1: J = 4 items / M = 2 modalities
** Scenario 1: J = 4 items / M = 2 modalities
* Scenario 1A : H_0 is TRUE
* Scenario 1A : H_0 is TRUE
clear
import delim "`path_data'/scenario_1A_100.csv", encoding(ISO-8859-2) case(preserve) clear
rename TT tt
clear
import delim "`path_data'/scenario_5A_100.csv", encoding(ISO-8859-2) case(preserve) clear
rename TT tt
keep if replication==1
di `k'
gsem (1.item1<-THETA@1)///
(1.item2<-THETA@1)///
(1.item3<-THETA@1)///
(1.item4<-THETA@1)///
(1.item5<-THETA@1)///
(1.item6<-THETA@1)///
(1.item7<-THETA@1)///
(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent
keep if replication==1
di `k'
* log using gsem.txt, text replace
* Créer une matrice 1000xnbitems+1 (pour beta) à l'avance et populer chaque coefficient à la main à chaque itération
* Créer une deuxième matrice et faire de même pour les std error
gsem (1.item1<-THETA@1)///
(1.item2<-THETA@1 tt)///
(1.item3<-THETA@1)///
(1.item4<-THETA@1)///
(THETA<-tt), mlogit tol(0.01) iterate(500) latent(THETA) nocapslatent
mat V=r(table)
mat W=V[1..2,1...]
putexcel set "W.xls", sheet("W") replace
putexcel A1=matrix(W)
* log close
pcm item1 item2 item3 item4, categorical(tt)